Other Teaching & AcademicsTrending Courses

IDENTIFICATION, ESTIMATION, AND LEARNING

Description

This course supplies a broad theoretical foundation for system identification, estimation, and studying. College students will research least squares estimation and its convergence properties, Kalman filters, noise dynamics and system illustration, perform approximation concept, neural nets, radial foundation features, wavelets, Volterra expansions, informative information units, persistent excitation, asymptotic variance, central restrict theorems, mannequin construction choice, system order estimate, most chance, unbiased estimates, Cramer-Rao decrease sure, Kullback-Leibler info distance, Akaike’s info criterion, experiment design, and mannequin validation.


0

Free


Get Coupon



Join us on telegram for Course Updates


Join Whatsapp Group for Daily Free Courses

Leave a Reply

Your email address will not be published. Required fields are marked *